US20230274430A1 - Information processing apparatus, information processing method, and program - Google Patents

Information processing apparatus, information processing method, and program Download PDF

Info

Publication number
US20230274430A1
US20230274430A1 US18/312,023 US202318312023A US2023274430A1 US 20230274430 A1 US20230274430 A1 US 20230274430A1 US 202318312023 A US202318312023 A US 202318312023A US 2023274430 A1 US2023274430 A1 US 2023274430A1
Authority
US
United States
Prior art keywords
blood vessel
artery
vein
ultrasound
vessel region
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
US18/312,023
Other languages
English (en)
Inventor
Tsuyoshi Matsumoto
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fujifilm Corp
Original Assignee
Fujifilm Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fujifilm Corp filed Critical Fujifilm Corp
Assigned to FUJIFILM CORPORATION reassignment FUJIFILM CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MATSUMOTO, TSUYOSHI
Publication of US20230274430A1 publication Critical patent/US20230274430A1/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0833—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures
    • A61B8/085—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures for locating body or organic structures, e.g. tumours, calculi, blood vessels, nodules
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/46—Ultrasonic, sonic or infrasonic diagnostic devices with special arrangements for interfacing with the operator or the patient
    • A61B8/461—Displaying means of special interest
    • A61B8/463—Displaying means of special interest characterised by displaying multiple images or images and diagnostic data on one display
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/761—Proximity, similarity or dissimilarity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/44—Constructional features of the ultrasonic, sonic or infrasonic diagnostic device
    • A61B8/4427—Device being portable or laptop-like
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5207—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of raw data to produce diagnostic data, e.g. for generating an image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/14—Digital output to display device ; Cooperation and interconnection of the display device with other functional units
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10132—Ultrasound image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2380/00—Specific applications
    • G09G2380/08—Biomedical applications

Definitions

  • a technique of the present disclosure relates to an information processing apparatus, an information processing method, and a program.
  • an ultrasound diagnostic apparatus has been known as an apparatus that obtains an image of the inside of a subject.
  • an ultrasound diagnostic apparatus includes an ultrasound probe provided with a transducer array in which a plurality of ultrasound transducers are arranged.
  • the ultrasound probe transmits ultrasound beams from the transducer array toward the inside of the subject in a state of being in contact with a body surface of the subject, and receives ultrasound echoes from the subject by the transducer array. Thereby, an electric signal corresponding to the ultrasound echoes is acquired. Further, the ultrasound diagnostic apparatus generates an ultrasound image for the corresponding portion of the subject by processing the acquired electric signal.
  • a technique for inserting a so-called puncture needle into a blood vessel of a subject while observing the inside of the subject using an ultrasound diagnostic apparatus is known.
  • an operator usually needs to recognize positions, shapes, and the like of blood vessels included in an ultrasound image by confirming the ultrasound image.
  • a certain level of proficiency is required.
  • a technique of automatically detecting blood vessels included in an ultrasound image and presenting the detected blood vessels to an operator is proposed (refer to, for example, JP2017-524455A).
  • artery/vein determination In puncture, an operator needs to accurately determine whether a blood vessel is an artery or a vein based on the ultrasound image. Hereinafter, the determination will be referred to as artery/vein determination.
  • artery/vein determination of a blood vessel by information processing such as image analysis based on the ultrasound image.
  • information processing such as image analysis based on the ultrasound image.
  • the determination is likely to be erroneous when shapes and the like of arteries and veins are similar.
  • An object of the technique of the present disclosure is to provide an information processing apparatus, an information processing method, and a program capable of improving accuracy of artery/vein determination of a blood vessel.
  • an information processing apparatus that performs processing on an ultrasound image, which is generated by transmitting ultrasound beams from a transducer array toward the inside of a living body and receiving ultrasound echoes generated in the living body, the apparatus including: a blood vessel detection unit that detects a blood vessel region including a blood vessel from the ultrasound image; a structure detection unit that detects a structure other than a blood vessel from the ultrasound image; and an artery/vein determination unit that determines whether the blood vessel included in the blood vessel region is an artery or a vein based on a relative positional relationship between the blood vessel region and the structure.
  • the information processing apparatus further includes: a highlight display unit that displays the blood vessel region in the ultrasound image displayed on a display device such that the blood vessel included in the blood vessel region is identified as an artery or a vein.
  • a highlight display unit that displays the blood vessel region in the ultrasound image displayed on a display device such that the blood vessel included in the blood vessel region is identified as an artery or a vein.
  • the blood vessel detection unit determines whether the blood vessel included in the blood vessel region is an artery or a vein, in addition to detection of the blood vessel region.
  • the information processing apparatus further includes: a correction unit that corrects a result of artery/vein determination by the blood vessel detection unit based on a result of artery/vein determination by the artery/vein determination unit.
  • the correction unit compares reliability of artery/vein determination by the blood vessel detection unit with reliability of artery/vein determination by the artery/vein determination unit, and selects a determination result having higher reliability.
  • the highlight display unit displays, on the display device, reliability on the determination result selected by the correction unit.
  • the highlight display unit displays, on the display device, a message urging an operator to pay attention in a case where the reliability on the determination result selected by the correction unit is lower than a certain value.
  • an information processing method for performing processing on an ultrasound image which is generated by transmitting ultrasound beams from a transducer array toward the inside of a living body and receiving ultrasound echoes generated in the living body, the method including: detecting a blood vessel region including a blood vessel from the ultrasound image; detecting a structure other than a blood vessel from the ultrasound image; and determining whether the blood vessel included in the blood vessel region is an artery or a vein based on a relative positional relationship between the blood vessel region and the structure.
  • a program causing a computer to execute a process for performing processing on an ultrasound image, which is generated by transmitting ultrasound beams from a transducer array toward the inside of a living body and receiving ultrasound echoes generated in the living body, the process including: detecting a blood vessel region including a blood vessel from the ultrasound image; detecting a structure other than a blood vessel from the ultrasound image; and determining whether the blood vessel included in the blood vessel region is an artery or a vein based on a relative positional relationship between the blood vessel region and the structure.
  • an information processing apparatus an information processing method, and a program capable of improving accuracy of artery/vein determination of a blood vessel.
  • FIG. 1 is an external view illustrating an example of a configuration of an ultrasound diagnostic apparatus according to a first embodiment
  • FIG. 2 is a diagram illustrating an example of an echo-guided puncture method
  • FIG. 3 is a block diagram illustrating an example of a configuration of the ultrasound diagnostic apparatus
  • FIG. 4 is a block diagram illustrating an example of a configuration of a reception circuit
  • FIG. 5 is a block diagram illustrating an example of a configuration of an image generation unit
  • FIG. 6 is a block diagram illustrating an example of a configuration of an image analysis unit
  • FIG. 7 is a diagram illustrating an example of blood vessel detection processing
  • FIG. 8 is a diagram illustrating an example of a training phase in which a blood vessel detection model is trained
  • FIG. 9 is a diagram illustrating an example of structure detection processing
  • FIG. 10 is a diagram illustrating an example of a training phase in which a structure detection model is trained
  • FIG. 11 is a diagram illustrating an example of artery/vein determination processing
  • FIG. 12 is a diagram illustrating an example of correction processing
  • FIG. 13 is a diagram illustrating an example of highlight display processing
  • FIG. 14 is a flowchart illustrating an example of an operation of the ultrasound diagnostic apparatus
  • FIG. 15 is a diagram illustrating an example of blood vessel detection processing for another ultrasound image
  • FIG. 16 is a diagram illustrating an example of structure detection processing for another ultrasound image
  • FIG. 17 is a diagram illustrating an example of artery/vein determination processing for another ultrasound image
  • FIG. 18 is a diagram illustrating an example of correction processing for another ultrasound image
  • FIG. 19 is a diagram illustrating an example of highlight display processing for another ultrasound image
  • FIG. 20 is a diagram illustrating a modification example of artery/vein determination processing
  • FIG. 21 is a diagram illustrating a modification example of artery/vein determination processing
  • FIG. 22 is a diagram illustrating an example of displaying a score
  • FIG. 23 is a diagram illustrating an example of displaying a message urging an operator to pay attention
  • FIG. 24 is a diagram illustrating a first modification example of the ultrasound diagnostic apparatus.
  • FIG. 25 is a diagram illustrating a second modification example of the ultrasound diagnostic apparatus.
  • FIG. 1 illustrates an example of a configuration of an ultrasound diagnostic apparatus 2 according to the technique of the present disclosure.
  • the ultrasound diagnostic apparatus 2 according to the present embodiment includes an ultrasound probe 10 and an apparatus main body 20 .
  • the ultrasound probe 10 is held by an operator and is brought into contact with a surface of a living body to be measured.
  • the ultrasound probe 10 transmits and receives ultrasound beams UBs to and from the inside of the living body.
  • the apparatus main body 20 is, for example, a smartphone, a tablet terminal, or the like. By installing a program such as application software in the apparatus main body 20 , the apparatus main body 20 performs imaging of a signal or the like which is output from the ultrasound probe 10 .
  • the ultrasound probe 10 and the apparatus main body 20 perform wireless communication with each other by, for example, WiFi or Bluetooth (registered trademark).
  • the apparatus main body 20 is not limited to a mobile terminal such as a smartphone or a tablet terminal, and may be a personal computer (PC) or the like.
  • the apparatus main body 20 is an example of an “information processing apparatus” according to the technique of the present disclosure.
  • the ultrasound probe 10 includes a housing 11 .
  • the housing 11 is configured by an array housing part 11 A and a grip portion 11 B.
  • the array housing part 11 A houses a transducer array 13 (refer to FIG. 3 ).
  • the grip portion 11 B is connected to the array housing part 11 A, and is gripped by the operator.
  • a direction from the grip portion 11 B toward the array housing part 11 A is defined as a +Y direction
  • a width direction of the ultrasound probe 10 orthogonal to the Y direction is defined as an X direction
  • a direction orthogonal to the X direction and the Y direction (that is, a thickness direction of the ultrasound probe 10 ) is defined as a Z direction.
  • An acoustic lens is disposed at an end portion of the array housing part 11 A in the +Y direction.
  • a so-called acoustic matching layer (not illustrated) is disposed on the transducer array 13 , and the acoustic lens is disposed on the acoustic matching layer.
  • a plurality of transducers included in the transducer array 13 are linearly arranged along the X direction. That is, the ultrasound probe 10 according to the present embodiment has a linear type, and linearly transmits ultrasound beams UBs.
  • the ultrasound probe 10 may have a convex type in which the transducer array 13 is disposed in a convex curved shape. In this case, the ultrasound probe 10 radially transmits ultrasound beams UBs. Further, the ultrasound probe 10 may have a sector type.
  • a linear guide marker M extending along the Y direction is attached to an outer peripheral portion of the array housing part 11 A.
  • the guide marker M is used as a guide when the operator brings the ultrasound probe 10 into contact with a living body.
  • the apparatus main body 20 includes a display device 21 for displaying an ultrasound image based on a signal transmitted from the ultrasound probe 10 .
  • the display device 21 is, for example, a display device such as an organic electro-luminescence (organic EL) display or a liquid crystal display.
  • organic EL organic electro-luminescence
  • a touch panel is incorporated in the display device 21 . The operator can perform various operations on the apparatus main body 20 by using the touch panel.
  • FIG. 2 is a diagram illustrating an example of an echo-guided puncture method.
  • the ultrasound probe 10 is used when the operator punctures a puncture needle 31 into a blood vessel B in a living body 30 while checking an ultrasound image displayed on the apparatus main body 20 .
  • the living body 30 is, for example, an arm of a person.
  • the ultrasound probe 10 is brought into contact with the surface of the living body 30 such that the width direction (that is, the X direction) of the ultrasound probe 10 crosses a traveling direction of the blood vessel B. This procedure is called a short-axis method (or crossing method).
  • a cross section of the blood vessel B is displayed in the ultrasound image.
  • an anatomical structure (hereinafter, simply referred to as a structure) is present in the living body 30 .
  • the structure is, for example, a biological tissue such as a tendon, a bone, a nerve, or a muscle.
  • the types and features of the structures included in the living body 30 differ depending on the parts (arms, legs, abdomen, and the like) of the living body 30 .
  • the apparatus main body 20 supports puncturing by the operator by detecting a blood vessel from the ultrasound image, performing artery/vein determination of the blood vessel, and displays a result of the artery/vein determination in the ultrasound image displayed on the display device 21 .
  • FIG. 3 illustrates an example of a configuration of the ultrasound diagnostic apparatus 2 .
  • the ultrasound probe 10 includes a transducer array 13 , a transmission/reception circuit 14 , and a communication unit 15 .
  • the transmission/reception circuit 14 includes a transmission circuit 16 and a reception circuit 17 .
  • the transmission circuit 16 and the reception circuit 17 are respectively connected to the transducer array 13 .
  • the transmission/reception circuit 14 transmits and receives signals to and from a processor 25 of the apparatus main body 20 via the communication unit 15 .
  • the transducer array 13 includes a plurality of transducers (not illustrated) which are arranged in one-dimensional manner or two-dimensional manner. Each of these transducers transmits ultrasound beams UBs in accordance with a drive signal supplied from the transmission circuit 16 and receives ultrasound echoes from the living body 30 . The transducer outputs a signal based on the received ultrasound echoes.
  • the transducer is configured, for example, by forming electrodes at both ends of a piezoelectric body.
  • the piezoelectric body includes a piezoelectric ceramic represented by lead zirconate titanate (PZT), a polymer piezoelectric element represented by poly vinylidene di fluoride (PVDF), a piezoelectric single crystal represented by lead magnesium niobate-lead titanate (PMN-PT), and the like.
  • PZT lead zirconate titanate
  • PVDF poly vinylidene di fluoride
  • PMN-PT lead magnesium niobate-lead titanate
  • the transmission circuit 16 includes, for example, a plurality of pulse generators.
  • the transmission circuit 16 adjusts a delay amount of a drive signal based on a transmission delay pattern, which is selected according to a control signal transmitted from the processor 25 of the apparatus main body 20 , and supplies the adjusted delay amount of the drive signal to the plurality of transducers included in the transducer array 13 .
  • the delay amount of the drive signal is adjusted by the transmission circuit 16 such that the ultrasound waves transmitted from the plurality of transducers form the ultrasound beams UBs.
  • the drive signal is a pulsed or continuous voltage signal. In a case where the drive signal is applied, the transducers transmit pulsed or continuous ultrasound waves by expansion and contraction. By combining the ultrasound waves transmitted from the plurality of transducers, the ultrasound beams UBs as combined waves are formed.
  • the ultrasound beams UBs are transmitted into the living body 30 , the ultrasound beams UBs are reflected by a part such as a blood vessel B in the living body 30 . Thereby, ultrasound echoes are generated, and the ultrasound echoes propagate toward the transducer array 13 .
  • the ultrasound echoes which propagate toward the transducer array 13 in this way are received by the plurality of transducers included in the transducer array 13 .
  • the transducers In a case where the ultrasound echoes are received, the transducers generate electric signals by expansion and contraction. The electric signals generated by the transducers are output to the reception circuit 17 .
  • the reception circuit 17 generates a sound wave signal by processing the electric signals output from the transducer array 13 according to a control signal transmitted from the processor 25 of the apparatus main body 20 .
  • the reception circuit 17 is configured by connecting an amplification unit 41 , an analog to digital (A/D) conversion unit 42 , and a beam former 43 in series.
  • the amplification unit 41 amplifies the signal which is input from each of the plurality of transducers included in the transducer array 13 , and transmits the amplified signal to the A/D conversion unit 42 .
  • the A/D conversion unit 42 converts the signal transmitted from the amplification unit 41 into digital reception data, and transmits the converted reception data to the beam former 43 .
  • the beam former 43 adds a delay to the reception data converted by the A/D conversion unit 42 according to a sound velocity or a sound velocity distribution which is set based on a reception delay pattern selected according to a control signal transmitted from the processor 25 of the apparatus main body 20 .
  • This addition processing is referred to as reception focus processing.
  • reception focus processing a sound wave signal, which is obtained by performing phasing addition on the reception data converted by the A/D conversion unit 42 and narrowing down a focus of the ultrasound echo, is acquired.
  • the apparatus main body 20 includes a display device 21 , an input device 22 , a communication unit 23 , a storage device 24 , and a processor 25 .
  • the input device 22 is, for example, a touch panel or the like incorporated in the display device 21 .
  • the input device 22 may be a keyboard, a mouse, a track ball, a touch pad, or the like.
  • the communication unit 23 performs wireless communication with the communication unit 15 of the ultrasound probe 10 .
  • the input device 22 and the storage device 24 are connected to the processor 25 .
  • the processor 25 and the storage device 24 are connected to each other so as to be able to bidirectionally exchange information.
  • the storage device 24 is a device that stores a program 26 or the like for operating the ultrasound diagnostic apparatus 2 , and is, for example, a flash memory, a hard disc drive (HDD), or a solid state drive (SSD).
  • a recording medium such as a flexible disc (FD), a magneto-optical (MO) disc, a magnetic tape, a compact disc (CD), a digital versatile disc (DVD), a secure digital (SD) card, or a Universal Serial Bus (USB) memory, a server, or the like can be used.
  • the processor 25 is, for example, a central processing unit (CPU).
  • the processor 25 performs processing based on the program 26 in cooperation with a random access memory (RAM) (not illustrated) or the like, and thus the apparatus main body 20 functions as a main control unit 50 , an image generation unit 51 , a display control unit 52 , an image analysis unit 53 , and a highlight display unit 54 .
  • RAM random access memory
  • the processor 25 is not limited to the CPU.
  • the processor 25 may be configured by a field programmable gate array (FPGA), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a graphics processing unit (GPU), or another integrated circuit (IC), or may be configured by a combination thereof.
  • FPGA field programmable gate array
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • GPU graphics processing unit
  • IC integrated circuit
  • the main control unit 50 controls each unit of the ultrasound diagnostic apparatus 2 based on an input operation by the operator via the input device 22 .
  • the main control unit 50 transmits the above-described control signal to the ultrasound probe 10 via the communication unit 23 .
  • the sound wave signal generated by the reception circuit 17 is input from the ultrasound probe 10 to the processor 25 via the communication unit 23 .
  • the image generation unit 51 acquires the sound wave signal which is input from the ultrasound probe 10 under a control of the main control unit 50 , and generates an ultrasound image U based on the acquired sound wave signal. As illustrated in FIG. 5 as an example, the image generation unit 51 is configured by connecting a signal processing unit 61 , a digital scan converter (DSC) 62 , and an image processing unit 63 in series.
  • DSC digital scan converter
  • the signal processing unit 61 performs, on the sound wave signal generated by the reception circuit 17 , correction of attenuation due to a distance according to a depth of a reflection position of the ultrasound wave, and then performs envelope detection processing on the corrected sound wave signal. Thereby, a B-mode image signal, which is tomographic image information on a tissue in the subject, is generated.
  • the DSC 62 converts (so-called raster-converts) the B mode image signal generated by the signal processing unit 61 into an image signal conforming to a normal television signal scanning method.
  • the image processing unit 63 performs various image processing such as gradation processing on the B mode image signal which is input from the DSC 62 , and then outputs the B mode image signal to the display control unit 52 and the image analysis unit 53 .
  • the B mode image signal obtained by performing image processing by the image processing unit 63 is simply referred to as an ultrasound image U.
  • the transmission/reception circuit 14 of the ultrasound probe 10 and the image generation unit 51 are controlled by the main control unit 50 such that the ultrasound image U is periodically generated at a constant frame rate.
  • the transmission/reception circuit 14 and the image generation unit 51 function as an image acquisition unit that acquires the ultrasound image U.
  • the display control unit 52 Under the control of the main control unit 50 , the display control unit 52 performs predetermined processing on the ultrasound image U generated by the image generation unit 51 , and causes the display device 21 to display the processed ultrasound image U.
  • the image analysis unit 53 Under the control of the main control unit 50 , the image analysis unit 53 generates blood vessel information DB by performing image analysis on the ultrasound image U which is input from the image generation unit 51 , and outputs the generated blood vessel information DB to the highlight display unit 54 .
  • the blood vessel information DB includes, for example, a detection result of a blood vessel region included in the ultrasound image U and a result of artery/vein determination of the detected blood vessel.
  • the highlight display unit 54 controls the display control unit 52 based on the blood vessel information DB which is input from the image analysis unit 53 under the control of the main control unit 50 . Thereby, the blood vessel region is highlighted and displayed in the ultrasound image U displayed on the display device 21 . In addition, the highlight display unit 54 displays the blood vessel region based on the artery/vein determination result such that the blood vessel included in the blood vessel region can be identified as an artery or a vein.
  • the image analysis unit 53 includes a blood vessel detection unit 71 , a structure detection unit 72 , an artery/vein determination unit 73 , and a correction unit 74 .
  • the ultrasound image U generated by the image generation unit 51 is input to the blood vessel detection unit 71 and the structure detection unit 72 .
  • the blood vessel detection unit 71 specifies a blood vessel region by individually detecting each blood vessel included in the ultrasound image U, and performs artery/vein determination of the blood vessel included in the blood vessel region.
  • the blood vessel detection unit 71 outputs information including a detection result of a blood vessel region and an artery/vein determination result of the blood vessel region to the correction unit 74 and the artery/vein determination unit 73 , as blood vessel detection information D 1 .
  • At least information on the blood vessel region detected by the blood vessel detection unit 71 may be input to the artery/vein determination unit 73 .
  • the structure detection unit 72 detects a structure region including a structure such as a tendon, a bone, a nerve, or a muscle based on the ultrasound image U, and outputs, as structure detection information D 2 , information representing the detected structure region to the artery/vein determination unit 73 .
  • the artery/vein determination unit 73 performs artery/vein determination of the blood vessel included in the blood vessel region based on an anatomical relative positional relationship between the blood vessel region included in the blood vessel detection information D 1 and the structure region included in the structure detection information D 2 .
  • the artery/vein determination unit 73 sets the structure region as a landmark, and performs artery/vein determination based on a relative positional relationship of the blood vessels when the landmark is set as a reference.
  • the artery/vein determination unit 73 outputs, as artery/vein determination information D 3 , information representing a result of the artery/vein determination to the correction unit 74 .
  • the correction unit 74 corrects the artery/vein determination result included in the blood vessel detection information D 1 based on the artery/vein determination information D 3 .
  • the correction unit 74 outputs, as the above-described blood vessel information DB, the corrected blood vessel detection information D 1 to the highlight display unit 54 .
  • FIG. 7 illustrates an example of blood vessel detection processing by the blood vessel detection unit 71 .
  • the blood vessel detection unit 71 performs processing of detecting a blood vessel region Ra including a blood vessel B from the ultrasound image U by using a known algorithm, and performs artery/vein determination of the blood vessel B included in the blood vessel region Ra.
  • the blood vessel region Ra includes a blood vessel B determined as an artery
  • the blood vessel region Ra is indicated by a broken line.
  • the blood vessel region Ra includes a blood vessel B determined as a vein
  • the blood vessel region Ra is indicated by a solid line.
  • the blood vessel region Ra illustrated in FIG. 7 includes a blood vessel B determined as an artery.
  • the blood vessel detection unit 71 detects the blood vessel region Ra for each of the blood vessels B.
  • a “label” representing an artery/vein determination result and a “score” representing reliability (that is, certainty) of the artery/vein determination result are associated with the blood vessel region Ra.
  • the label represents whether the blood vessel B included in the blood vessel region Ra is an “artery” or a “vein”.
  • the score is a value in a range equal to or larger than 0 and equal to or smaller than 1. As the score is closer to 1, the reliability is higher.
  • the blood vessel region Ra associated with the label and the score corresponds to the above-described blood vessel detection information D 1 .
  • an extensor carpi radialis longus hereinafter, referred to as ECRL
  • an extensor carpi radialis brevis hereinafter, referred to as ECRB
  • the ECRL and the ECRB are examples of structures.
  • the blood vessel detection unit 71 performs blood vessel detection processing using a blood vessel detection model 71 A (refer to FIG. 8 ), which is a trained model generated by machine learning.
  • the blood vessel detection model 71 A is, for example, an object detection algorithm using deep learning.
  • an object detection model configured by regional CNN (R-CNN), which is a kind of convolutional neural network (CNN), can be used.
  • the blood vessel detection model 71 A detects, as an object, a region including a blood vessel single-body from the ultrasound image U, and determines a label for the detected region. In addition, the blood vessel detection model 71 A outputs information representing the detected blood vessel region Ra together with a label and a score.
  • FIG. 8 is a diagram illustrating an example of a training phase in which the blood vessel detection model 71 A is trained by machine learning.
  • the blood vessel detection model 71 A performs training using training data TD 1 .
  • the training data TD 1 includes a plurality of training images P associated with correct answer labels L.
  • the training image P included in the training data TD 1 is a sample image of a blood vessel single-body (artery and vein).
  • the training data TD 1 includes various training images Pin which blood vessels have different shapes, sizes, and the like.
  • the training image P is input to the blood vessel detection model 71 A.
  • the blood vessel detection model 71 A outputs a determination result A of the training image P.
  • Loss calculation is performed using a loss function based on the determination result A and the correct answer label L.
  • update setting of various coefficients of the blood vessel detection model 71 A is performed according to a result of the loss calculation, and the blood vessel detection model 71 A is updated according to the update setting.
  • a series of processing which includes inputting of the training image P to the blood vessel detection model 71 A, outputting of the determination result A from the blood vessel detection model 71 A, the loss calculation, the update setting, and updating of the blood vessel detection model 71 A, is repeatedly performed.
  • the repetition of the series of processing is ended in a case where detection accuracy reaches a predetermined setting level.
  • the blood vessel detection model 71 A of which the detection accuracy reaches the setting level is stored in the storage device 24 , and then is used by the blood vessel detection unit 71 in the blood vessel detection processing which is in an operation phase.
  • FIG. 9 illustrates an example of structure detection processing by the structure detection unit 72 .
  • the structure detection unit 72 performs processing of detecting a structure region Rb including a structure from the ultrasound image U by using a known algorithm.
  • the structure detection unit 72 performs structure detection processing using a structure detection model 72 A (refer to FIG. 10 ), which is a trained model generated by machine learning.
  • the structure detection model 72 A is, for example, an object detection algorithm using deep learning.
  • As the structure detection model 72 A for example, an object detection model configured by R-CNN, which is a kind of CNN, can be used.
  • the structure detection unit 72 detects, as an object, a structure region Rb including a structure from the ultrasound image U.
  • the information representing the structure region Rb corresponds to the structure detection information D 2 described above.
  • the structure detection unit 72 detects, as the structure region Rb, a region including the ECRL and the ECRB.
  • the structure detection unit 72 may individually detect, as the structure regions Rb, the region including the ECRL and the region including the ECRB.
  • FIG. 10 is a diagram illustrating an example of a training phase in which the structure detection model 72 A is trained by machine learning.
  • the structure detection model 72 A performs training using training data TD 2 .
  • the training data TD 2 includes a plurality of training images P associated with correct answer labels L.
  • the training image P included in the training data TD 2 is a sample image of a structure.
  • the training data TD 2 includes training images P of various structures having different types (such as tendons, bones, nerves, or muscles), numbers, shapes, sizes, textures, and the like of biological tissues.
  • the training image P is input to the structure detection model 72 A.
  • the structure detection model 72 A outputs a determination result A of the training image P. Loss calculation is performed using a loss function based on the determination result A and the correct answer label L.
  • update setting of various coefficients of the structure detection model 72 A is performed according to a result of the loss calculation, and the structure detection model 72 A is updated according to the update setting.
  • a series of processing which includes inputting of the training image P to the structure detection model 72 A, outputting of the determination result A from the structure detection model 72 A, the loss calculation, the update setting, and updating of the structure detection model 72 A, is repeatedly performed.
  • the repetition of the series of processing is ended in a case where detection accuracy reaches a predetermined setting level.
  • the structure detection model 72 A of which the detection accuracy reaches the setting level is stored in the storage device 24 , and then is used by the structure detection unit 72 in the structure detection processing which is in an operation phase.
  • FIG. 11 illustrates an example of artery/vein determination processing by the artery/vein determination unit 73 .
  • the artery/vein determination unit 73 performs artery/vein determination of the blood vessel B included in the blood vessel region Ra based on an anatomical relative positional relationship between the blood vessel region Ra included in the blood vessel detection information D 1 and the structure region Rb included in the structure detection information D 2 .
  • the artery/vein determination unit 73 obtains, as a label for the blood vessel B, a score for each of “artery” and “vein”, and selects the label having a higher score.
  • the artery/vein determination unit 73 generates artery/vein determination information D 3 by obtaining the label and the score for the blood vessel B included in the blood vessel region Ra.
  • the artery/vein determination unit 73 performs artery/vein determination processing by using, for example, a trained model obtained by performing training using training data representing an anatomical relative positional relationship between the blood vessel region Ra and the structure region Rb.
  • the artery/vein determination unit 73 may perform artery/vein determination using known data representing an anatomical relative positional relationship.
  • the blood vessel region Ra illustrated in FIG. 11 is located on radialis (that is, a radius side) with respect to the structure region Rb including the ECRL and the ECRB, and thus the blood vessel B included in the blood vessel region Ra is determined as a vein (specifically, a cephalic vein).
  • artery/vein determination of the blood vessel is performed using the anatomical relative positional relationship between the blood vessel and the structure, and thus accuracy of the artery/vein determination is improved.
  • FIG. 12 illustrates an example of correction processing performed by the correction unit 74 .
  • the correction unit 74 compares, for the corresponding blood vessel B, the score included in the artery/vein determination information D 3 with the score included in the blood vessel detection information D 1 , and selects the label having a higher score. For example, in the example illustrated in FIG. 12 , for the blood vessel B, the score (0.90) included in the artery/vein determination information D 3 is higher than the score (0.75) included in the blood vessel detection information D 1 . Therefore, the correction unit 74 selects, as the label of the blood vessel B, the label (vein) included in the artery/vein determination information D 3 instead of the label (artery) included in the blood vessel detection information D 1 .
  • the correction unit 74 outputs, as the above-described blood vessel information DB, the corrected blood vessel detection information D 1 in which the label is corrected to the highlight display unit 54 .
  • the blood vessel information DB includes position information of the blood vessel region Ra in the ultrasound image U, and the label and the score for the blood vessel region Ra.
  • FIG. 13 illustrates an example of highlight display processing by the highlight display unit 54 .
  • the highlight display unit 54 displays the blood vessel region Ra in the ultrasound image U displayed on the display device 21 of the apparatus main body 20 based on the blood vessel information DB by using a rectangular frame.
  • the highlight display unit 54 displays the blood vessel region Ra based on the artery/vein determination result such that the blood vessel included in the blood vessel region Ra can be identified as an artery or a vein.
  • the blood vessel region Ra including a vein is indicated by a solid line
  • the blood vessel region Ra including an artery is indicated by a broken line.
  • the highlight display unit 54 may display the blood vessel region Ra such that the blood vessel region Ra can be identified according to a thickness of a line, a color of a line, brightness of a line, or the like without being limited to the line type.
  • the main control unit 50 determines whether or not a start operation is performed by the operator using the input device 22 or the like (step S 10 ). In a case where it is determined that a start operation is performed (YES in step S 10 ), the main control unit 50 generates the ultrasound image U by operating the transmission/reception circuit 14 of the ultrasound probe 10 and the image generation unit 51 (step S 11 ). The generated ultrasound image U is displayed on the display device 21 by the display control unit 52 .
  • the operator brings the ultrasound probe 10 into contact with the surface of the living body 30 .
  • the ultrasound beams UBs are transmitted from the transducer array 13 into the living body 30 according to the drive signal which is input from the transmission circuit 16 .
  • the ultrasound echo from the living body 30 is received by the transducer array 13 , and the received signal is output to the reception circuit 17 .
  • the received signal which is received by the reception circuit 17 is processed via the amplification unit 41 , the A/D conversion unit 42 , and the beam former 43 , and thus a sound wave signal is generated.
  • the sound wave signal is output to the apparatus main body 20 via the communication unit 15 .
  • the apparatus main body 20 receives the sound wave signal which is output from the ultrasound probe 10 via the communication unit 23 .
  • the sound wave signal which is received by the apparatus main body 20 is input to the image generation unit 51 .
  • a B-mode image signal is generated by performing envelope detection processing on the sound wave signal by the signal processing unit 61 , and the B-mode image signal is subjected to the DSC 62 and the image processing unit 63 .
  • an ultrasound image U is output to the display control unit 52 . Further, the ultrasound image U is output to the image analysis unit 53 .
  • the blood vessel detection processing (refer to FIG. 7 ) is performed by the blood vessel detection unit 71 (step S 12 ).
  • the blood vessel detection information D 1 generated by the blood vessel detection processing is output to the correction unit 74 and the artery/vein determination unit 73 .
  • step S 13 is performed in parallel with step S 12 .
  • the structure detection processing (refer to FIG. 9 ) is performed by the structure detection unit 72 .
  • the structure detection information D 2 generated by the structure detection processing is output to the artery/vein determination unit 73 .
  • the artery/vein determination processing (refer to FIG. 11 ) is performed by the artery/vein determination unit 73 .
  • the artery/vein determination information D 3 generated by the artery/vein determination processing is output to the correction unit 74 .
  • the correction processing (refer to FIG. 12 ) is performed by the correction unit 74 (step S 15 ).
  • the correction processing the label for the blood vessel region Ra included in the blood vessel detection information D 1 is corrected based on the artery/vein determination information D 3 .
  • the blood vessel information DB is output to the highlight display unit 54 .
  • the highlight display processing (refer to FIG. 13 ) is performed by the highlight display unit 54 (step S 16 ).
  • the highlight display processing is performed by the highlight display unit 54 (step S 16 ).
  • the blood vessel region Ra is highlighted and displayed in the ultrasound image U displayed on the display device 21 .
  • the blood vessel region Ra is displayed such that the blood vessel included in the blood vessel region Ra can be identified as an artery or a vein. In this way, by performing highlight display, the operator can accurately recognize the position of the blood vessel in the ultrasound image U, and can accurately recognize whether the blood vessel is an artery or a vein.
  • the main control unit 50 determines whether or not an end operation is performed by the operator using the input device 22 or the like (step S 17 ). In a case where it is determined that an end operation is not performed (NO in step S 17 ), the main control unit 50 returns the processing to step S 11 . Thereby, a new ultrasound image U is generated. On the other hand, in a case where it is determined that an end operation is performed (YES in step S 17 ), the main control unit 50 ends the operation of the ultrasound diagnostic apparatus 2 .
  • a blood vessel is detected by blood vessel detection processing, and artery/vein determination is individually performed on the detected blood vessel.
  • an error often occurs in the artery/vein determination of the blood vessel, and a result of the artery/vein determination may change for each frame.
  • the operator attempts to perform puncture based on the result of the artery/vein determination, the blood vessel to be punctured may be mistaken.
  • artery/vein determination of the blood vessel is performed using the anatomical relative positional relationship between the blood vessel and the structure which are detected from the ultrasound image, and thus accuracy of the artery/vein determination is improved.
  • the operator can accurately recognize the blood vessel (for example, a vein) to be punctured.
  • APL abductor pollicis longus
  • apophysis radius styloid process
  • the blood vessel detection unit 71 detects, as the blood vessel region Ra, each of the region including the blood vessel B 1 and the region including the blood vessel B 2 in the ultrasound image U, and associates a label and a score with each of the blood vessel regions Ra.
  • the two blood vessel regions Ra associated with the label and the score correspond to the above-described blood vessel detection information D 1 .
  • the labels of the blood vessels B 1 and B 2 are both determined as a “vein”.
  • the structure detection unit 72 detects, as the structure region Rb, each of the region including the APL and the region including the apophysis in the ultrasound image U.
  • the information representing the two structure region Rb corresponds to the structure detection information D 2 described above.
  • the artery/vein determination unit 73 performs artery/vein determination on each of the two blood vessel regions Ra based on an anatomical relative positional relationship between the blood vessel region and the two structure regions Rb.
  • the artery/vein determination unit 73 generates artery/vein determination information D 3 by obtaining the label and the score for each of the blood vessels B 1 and B 2 .
  • the correction unit 74 compares the score included in the artery/vein determination information D 3 with the score included in the blood vessel detection information D 1 for each of the blood vessels B 1 and B 2 , and selects the label having a higher score.
  • the score included in the artery/vein determination information D 3 is higher than the score included in the blood vessel detection information D 1 , and thus the label included in the artery/vein determination information D 3 is selected.
  • the label of the blood vessel B 1 is corrected from “vein” to “artery”.
  • the blood vessel region Ra is highlighted and displayed in the ultrasound image U based on the corrected label.
  • the blood vessel region Ra including the blood vessel B 1 determined as “artery” is indicated by a broken line
  • the blood vessel region Ra including the blood vessel B 2 determined as “vein” is indicated by a solid line.
  • the artery/vein determination unit 73 obtains, as the label for the blood vessel B, a score for each of “artery” and “vein” in the artery/vein determination processing (refer to FIG. 11 ), and selects the label having a higher score.
  • a threshold value for a score may be set, and a label having a score equal to or higher than the threshold value may be selected.
  • both scores may be lower than the threshold value.
  • the threshold value corresponds to low accuracy of the artery/vein determination based on the relative positional relationship between the blood vessel and the structure.
  • the artery/vein determination unit 73 may stop artery/vein determination.
  • the highlight display unit 54 may display the blood vessel region Ra in the ultrasound image U without distinguishing whether the blood vessel region Ra is an “artery” or a “vein”. In this case, the highlight display unit 54 may simply display the blood vessel region Ra as a “blood vessel”.
  • the highlight display unit 54 may display the blood vessel region Ra in the ultrasound image U without distinguishing whether the blood vessel region Ra is an “artery” or a “vein”.
  • the highlight display unit 54 may perform highlight display based on the label included in the blood vessel detection information D 1 .
  • the highlight display unit 54 may display the score for the label selected by the correction unit 74 (that is, reliability for the determination result selected by the correction unit 74 ) in association with the blood vessel region Ra. Thereby, the operator can recognize the reliability of the artery/vein determination for each blood vessel.
  • the highlight display unit 54 may display a message urging the operator to pay attention in a case where the score for the label selected by the correction unit 74 (that is, reliability for the determination result selected by the correction unit 74 ) is lower than a certain value. Thereby, the operator can reliably recognize that reliability of the artery/vein determination is low and caution is required in the puncture.
  • the artery/vein determination unit 73 may change the criterion for the artery/vein determination according to a type or the like of the structure detected by the structure detection unit 72 . This is because, for example, in a case where the structure has anatomically typical features in relation to the blood vessel, there is a high possibility that the determination result is correct even when the score of the artery/vein determination is low.
  • the artery/vein determination unit 73 changes the threshold value for the score (refer to FIG. 21 ) according to, for example, a type or the like of the structure.
  • the threshold value is set to be lower than the threshold value in a case where the structure does not have anatomically typical features.
  • the criterion for the artery/vein determination is not limited to the threshold value for the score, and may be changed by changing the algorithm for the artery/vein determination.
  • the labels for the blood vessel are two types of “artery” and “vein”.
  • the labels may be further subdivided.
  • “vein” is subdivided into a “cephalic vein”, a “basilic vein”, and the like.
  • the artery/vein determination unit 73 can specify the type of the blood vessel in addition to the artery/vein determination.
  • the highlight display unit 54 may display the type of the blood vessel in association with the blood vessel region Ra.
  • the blood vessel detection unit 71 performs the artery/vein determination of the blood vessel.
  • the blood vessel detection unit 71 may perform only detection of the blood vessel region Ra without performing the artery/vein determination. In this case, the correction unit 74 that corrects the result of the artery/vein determination by the blood vessel detection unit 71 is not required.
  • the blood vessel detection unit 71 and the structure detection unit 72 are respectively configured by individual object detection models.
  • the blood vessel detection unit 71 and the structure detection unit 72 can be configured by one object detection model.
  • the object detection model may be trained using training data including a training image of the blood vessel single-body and a training image of the structure.
  • the blood vessel detection unit 71 , the structure detection unit 72 , and the artery/vein determination unit 73 can be configured by one object detection model.
  • the blood vessel detection unit 71 , the structure detection unit 72 , the artery/vein determination unit 73 , and the correction unit 74 can be configured by one object detection model.
  • the blood vessel detection unit 71 and the structure detection unit 72 are configured by an object detection model of a CNN.
  • the object detection model is not limited to the CNN, and segmentation or another general detection model may be used.
  • the object detection model including the blood vessel detection unit 71 and the structure detection unit 72 may be configured by an identifier that identifies an object based on an image feature amount such as AdaBoost or a support vector machine (SVM).
  • AdaBoost image feature amount
  • SVM support vector machine
  • the identifier may be trained based on the feature amount vector.
  • the blood vessel detection unit 71 and the structure detection unit 72 are not limited to the object detection model by machine learning, and may perform object detection by template matching.
  • the blood vessel detection unit 71 stores, as a template, typical pattern data of a blood vessel single-body in advance, and calculates a similarity to the pattern data while searching for the ultrasound images U by using the template.
  • the blood vessel detection unit 71 specifies, as a blood vessel region Ra, a portion where the similarity is equal to or higher than a certain level and is maximized.
  • the structure detection unit 72 stores, as a template, typical pattern data of a structure in advance, and calculates a similarity to the pattern data while searching for the ultrasound images U by using the template.
  • the structure detection unit 72 specifies, as a blood vessel region Ra, a portion where the similarity is equal to or higher than a certain level and is maximized.
  • the template may be a part of an actual ultrasound image, or may be an image drawn by modeling a blood vessel or a structure.
  • the ultrasound probe 10 and the apparatus main body 20 are connected by wireless communication. Instead, the ultrasound probe 10 and the apparatus main body 20 may be connected by wire.
  • the image generation unit 51 that generates an ultrasound image U based on the sound wave signal is provided in the apparatus main body 20 .
  • the image generation unit 51 may be provided in the ultrasound probe 10 .
  • the ultrasound probe 10 generates an ultrasound image U and outputs the ultrasound image U to the apparatus main body 20 .
  • the processor 25 of the apparatus main body 20 performs image analysis or the like based on the ultrasound image U which is input from the ultrasound probe 10 .
  • the display device 21 , the input device 22 , and the ultrasound probe 10 are directly connected to the processor 25 .
  • the display device 21 , the input device 22 , and the ultrasound probe 10 may be indirectly connected to the processor 25 via a network.
  • the display device 21 , the input device 22 , and the ultrasound probe 10 A are connected to the apparatus main body 20 A via a network NW.
  • the apparatus main body 20 A is obtained by removing the display device 21 and the input device 22 from the apparatus main body 20 according to the first embodiment and adding the transmission/reception circuit 14 , and is configured by the transmission/reception circuit 14 , the storage device 24 , and the processor 25 .
  • the ultrasound probe 10 A is obtained by removing the transmission/reception circuit 14 from the ultrasound probe 10 according to the first embodiment.
  • the display device 21 , the input device 22 , and the ultrasound probe 10 A are connected to the apparatus main body 20 A via the network NW, and thus the apparatus main body 20 A can be used as a so-called remote server.
  • the operator can prepare the display device 21 , the input device 22 , and the ultrasound probe 10 A at the operator's hand, and thus convenience is improved.
  • the display device 21 and the input device 22 are configured by a mobile terminal such as a smartphone or a tablet terminal, convenience is further improved.
  • the display device 21 and the input device 22 are provided in the apparatus main body 20 B, and the ultrasound probe 10 A is connected to the apparatus main body 20 B via the network NW.
  • the apparatus main body 20 B may be configured by a remote server.
  • the apparatus main body 20 B can be configured by a mobile terminal such as a smartphone or a tablet terminal.
  • the following various processors may be used as a hardware structure of processing units that perform various processing, such as the main control unit 50 , the image generation unit 51 , the display control unit 52 , the image analysis unit 53 , and the highlight display unit 54 .
  • the various processors include, as described above, a CPU which is a general-purpose processor that functions as various processing units by executing software (program 26 ), and a dedicated electric circuit which is a processor having a circuit configuration specifically designed to execute specific processing, such as a programmable logic device (PLD) or an ASIC that is a processor of which the circuit configuration may be changed after manufacturing such as a field programmable gate array (FPGA).
  • PLD programmable logic device
  • FPGA field programmable gate array
  • One processing unit may be configured by one of these various processors, or may be configured by a combination of two or more processors having the same type or different types (for example, a combination of a plurality of FPGAs and/or a combination of a CPU and an FPGA). Further, the plurality of processing units may be configured by one processor.
  • the plurality of processing units are configured by one processor
  • a computer such as a client and a server
  • a form in which one processor is configured by a combination of one or more CPUs and software and the processor functions as the plurality of processing units may be adopted.
  • SoC system on chip
  • a form in which a processor that realizes the function of the entire system including the plurality of processing units by one IC chip is used may be adopted.
  • the various processing units are configured by using one or more various processors as a hardware structure.
  • an electric circuit in which circuit elements such as semiconductor elements are combined may be used.
  • An information processing apparatus that performs processing on an ultrasound image, which is generated by transmitting ultrasound beams from a transducer array toward the inside of a living body and receiving ultrasound echoes generated in the living body, the apparatus including:
  • processor is configured to:
  • the blood vessel included in the blood vessel region is an artery or a vein based on a relative positional relationship between the blood vessel region and the structure.
  • the processor is configured to display the blood vessel region in the ultrasound image displayed on a display device such that the blood vessel included in the blood vessel region is identified as an artery or a vein.
  • the processor is configured to determine whether the blood vessel included in the blood vessel region is an artery or a vein based on the blood vessel region.
  • the processor is configured to correct a result of artery/vein determination based on the blood vessel region, based on a result of artery/vein determination based on a relative positional relationship between the blood vessel region and the structure.
  • the processor is configured to compare reliability of artery/vein determination based on the blood vessel region with reliability of artery/vein determination based on the relative positional relationship between the blood vessel region and the structure, and select a determination result having higher reliability.
  • the processor is configured to display, on the display device, reliability on the selected determination result.
  • the processor is configured to display, on the display device, a message urging an operator to pay attention in a case where the reliability on the selected determination result is lower than a certain value.
  • the technique of the present disclosure can also appropriately combine the various embodiments and/or the various modification examples.
  • the technique of the present disclosure is not limited to the embodiments, and various configurations may be adopted without departing from the scope of the present disclosure.
  • the described contents and the illustrated contents are detailed explanations of a part according to the technique of the present disclosure, and are merely examples of the technique of the present disclosure.
  • the descriptions related to the configuration, the function, the operation, and the effect are descriptions related to examples of a configuration, a function, an operation, and an effect of a part according to the technique of the present disclosure. Therefore, it goes without saying that, in the described contents and illustrated contents, unnecessary parts may be deleted, new components may be added, or replacements may be made without departing from the spirit of the technique of the present disclosure. Further, in order to avoid complications and facilitate understanding of the part according to the technique of the present disclosure, in the described contents and illustrated contents, descriptions of technical knowledge and the like that do not require particular explanations to enable implementation of the technique of the present disclosure are omitted.
  • a and/or B is synonymous with “at least one of A or B.” That is, “A and/or B” means that only A may be included, that only B may be included, or that a combination of A and B may be included.

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Evolutionary Computation (AREA)
  • Pathology (AREA)
  • Biophysics (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • Multimedia (AREA)
  • Quality & Reliability (AREA)
  • Human Computer Interaction (AREA)
  • General Engineering & Computer Science (AREA)
  • Vascular Medicine (AREA)
  • Physiology (AREA)
  • Ultra Sonic Daignosis Equipment (AREA)
US18/312,023 2020-11-19 2023-05-04 Information processing apparatus, information processing method, and program Pending US20230274430A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
JP2020-192722 2020-11-19
JP2020192722 2020-11-19
PCT/JP2021/034785 WO2022107441A1 (ja) 2020-11-19 2021-09-22 情報処理装置、情報処理方法、及びプログラム

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2021/034785 Continuation WO2022107441A1 (ja) 2020-11-19 2021-09-22 情報処理装置、情報処理方法、及びプログラム

Publications (1)

Publication Number Publication Date
US20230274430A1 true US20230274430A1 (en) 2023-08-31

Family

ID=81708841

Family Applications (1)

Application Number Title Priority Date Filing Date
US18/312,023 Pending US20230274430A1 (en) 2020-11-19 2023-05-04 Information processing apparatus, information processing method, and program

Country Status (5)

Country Link
US (1) US20230274430A1 (ja)
EP (1) EP4248879A4 (ja)
JP (1) JPWO2022107441A1 (ja)
CN (1) CN116528773A (ja)
WO (1) WO2022107441A1 (ja)

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7074187B2 (en) * 2002-12-13 2006-07-11 Selzer Robert H System and method for improving ultrasound image acquisition and replication for repeatable measurements of vascular structures
JP4812460B2 (ja) * 2006-02-22 2011-11-09 株式会社ユネクス 動脈血管判定方法および装置
US10231694B2 (en) * 2011-12-16 2019-03-19 Koninklijke Philips N.V. Automatic blood vessel identification by name
WO2013161228A1 (ja) * 2012-04-23 2013-10-31 パナソニック株式会社 超音波診断装置および超音波診断装置の制御方法
WO2014034148A1 (ja) * 2012-09-03 2014-03-06 パナソニック株式会社 超音波診断装置、超音波診断装置の制御方法および超音波診断装置の制御器
EP3277188B1 (en) 2015-04-03 2018-10-31 Koninklijke Philips N.V. Ultrasound system and method of vessel identification
EP3845134B1 (en) * 2018-08-27 2022-07-27 FUJIFILM Corporation Ultrasound diagnosis device and ultrasound diagnosis device control method
CN111134727B (zh) * 2018-11-02 2022-12-20 无锡祥生医疗科技股份有限公司 基于神经网络的静脉与动脉识别的穿刺引导系统
US20200229795A1 (en) * 2019-01-22 2020-07-23 General Electric Company Method and systems for color flow imaging of arteries and veins

Also Published As

Publication number Publication date
JPWO2022107441A1 (ja) 2022-05-27
EP4248879A4 (en) 2023-11-22
CN116528773A (zh) 2023-08-01
EP4248879A1 (en) 2023-09-27
WO2022107441A1 (ja) 2022-05-27

Similar Documents

Publication Publication Date Title
WO2014002963A1 (ja) 超音波診断装置及び画像処理方法
CN114364325B (zh) 超声波诊断装置及超声波诊断装置的控制方法
US11116475B2 (en) Ultrasound diagnostic apparatus and method for controlling ultrasound diagnostic apparatus
US20220142608A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20210128102A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20210077066A1 (en) Acoustic wave diagnostic apparatus and method of controlling acoustic wave diagnostic apparatus
US20220104791A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20210219960A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20220031288A1 (en) Ultrasound diagnostic apparatus, control method of ultrasound diagnostic apparatus, and processor for ultrasound diagnostic apparatus
US11759173B2 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
CN116471996A (zh) 信息处理装置、超声波诊断装置、信息处理方法及信息处理程序
US20230293144A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20230274430A1 (en) Information processing apparatus, information processing method, and program
US20230263505A1 (en) Information processing apparatus, information processing method, and program
JP7427497B2 (ja) 情報処理装置、情報処理方法、プログラムおよび超音波診断装置
US20240065671A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US11925506B2 (en) Ultrasonic image diagnostic apparatus, identifier changing method, and identifier changing program
US20230190238A1 (en) Ultrasound system and control method of ultrasound system
US20230363740A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20220370045A1 (en) Image generation device, image generation method, and program
US20230157662A1 (en) Ultrasound image analysis apparatus, ultrasound diagnostic apparatus, and control method for ultrasound image analysis apparatus
US20230181155A1 (en) Ultrasound diagnostic apparatus and control method for ultrasound diagnostic apparatus
EP4285836A1 (en) Ultrasound diagnostic apparatus and control method of ultrasound diagnostic apparatus
US20230293146A1 (en) Information processing apparatus, ultrasound diagnostic apparatus, information processing method, and information processing program
CN117898757A (zh) 双平面探头的插入深度预警方法及超声成像设备

Legal Events

Date Code Title Description
AS Assignment

Owner name: FUJIFILM CORPORATION, JAPAN

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MATSUMOTO, TSUYOSHI;REEL/FRAME:063533/0714

Effective date: 20230309

STPP Information on status: patent application and granting procedure in general

Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION